Structural and functional analysis of the 1:1 growth hormone:receptor complex reveals the molecular basis for receptor affinity

Alchemical Calculation of Relative Free Energies for Charge-Changing Mutations at Protein-Protein Interfaces Considering Fixed and Variable Protonation States

The calculation of relative free energies (ΔΔG) for charge-changing mutations at protein-protein interfaces through alchemical methods remains challenging due to variations in the system's net charge during charging steps, the possibility of mutated and contacting ionizable residues occurring in various protonation states, and undersampling issues. In this study, we present a set of strategies, collectively termed TIRST/TIRST-H+, to address some of these challenges. Our approaches combine thermodynamic integration (TI) with the prediction of pKa shifts to calculate ΔΔG values. Moreover, special sets of restraints are employed to keep the alchemically transformed molecules separated. The accuracy of the devised approaches was assessed on a large and diverse data set comprising 164 point mutations of charged residues (Asp, Glu, Lys, and Arg) to Ala at the protein-protein interfaces of complexes with known three-dimensional structures. Mean absolute and root-mean-square errors ranging from 1.38 to 1.66 and 1.89 to 2.44 kcal/mol, respectively, and Pearson correlation coefficients of ∼0.6 were obtained when testing the approaches on the selected data set using the GPU-TI module of Amber18 suite and the ff14SB force field. Furthermore, the inclusion of variable protonation states for the mutated acid residues improved the accuracy of the predicted ΔΔG values. Therefore, our results validate the use of TIRST/TIRST-H+ in prospective studies aimed at evaluating the impact of charge-changing mutations to Ala on the stability of protein-protein complexes.

Structural Modeling of Cytokine-Receptor-JAK2 Signaling Complexes Using AlphaFold Multimer

Homodimeric class 1 cytokine receptors include the erythropoietin (EPOR), thrombopoietin (TPOR), granulocyte colony-stimulating factor 3 (CSF3R), growth hormone (GHR), and prolactin receptors (PRLR). These cell-surface single-pass transmembrane (TM) glycoproteins regulate cell growth, proliferation, and differentiation and induce oncogenesis. An active TM signaling complex consists of a receptor homodimer, one or two ligands bound to the receptor extracellular domains, and two molecules of Janus Kinase 2 (JAK2) constitutively associated with the receptor intracellular domains. Although crystal structures of soluble extracellular domains with ligands have been obtained for all of the receptors except TPOR, little is known about the structure and dynamics of the complete TM complexes that activate the downstream JAK-STAT signaling pathway. Three-dimensional models of five human receptor complexes with cytokines and JAK2 were generated here by using AlphaFold Multimer. Given the large size of the complexes (from 3220 to 4074 residues), the modeling required a stepwise assembly from smaller parts, with selection and validation of the models through comparisons with published experimental data. The modeling of active and inactive complexes supports a general activation mechanism that involves ligand binding to a monomeric receptor followed by receptor dimerization and rotational movement of the receptor TM α-helices, causing proximity, dimerization, and activation of associated JAK2 subunits. The binding mode of two eltrombopag molecules to the TM α-helices of the active TPOR dimer was proposed. The models also help elucidate the molecular basis of oncogenic mutations that may involve a noncanonical activation route. Models equilibrated in explicit lipids of the plasma membrane are publicly available.

Structure and function of a dual antagonist of the human growth hormone and prolactin receptors with site-specific PEG conjugates

Human growth hormone (hGH) is a pituitary-derived endocrine protein that regulates several critical postnatal physiologic processes including growth, organ development, and metabolism. Following adulthood, GH is also a regulator of multiple pathologies like fibrosis, cancer, and diabetes. Therefore, there is a significant pharmaceutical interest in developing antagonists of hGH action. Currently, there is a single FDA-approved antagonist of the hGH receptor (hGHR) prescribed for treating patients with acromegaly and discovered in our laboratory almost 3 decades ago. Here, we present the first data on the structure and function of a new set of protein antagonists with the full range of hGH actions-dual antagonists of hGH binding to the GHR as well as that of hGH binding to the prolactin receptor. We describe the site-specific PEG conjugation, purification, and subsequent characterization using MALDI-TOF, size-exclusion chromatography, thermostability, and biochemical activity in terms of ELISA-based binding affinities with GHR and prolactin receptor. Moreover, these novel hGHR antagonists display distinct antagonism of GH-induced GHR intracellular signaling in vitro and marked reduction in hepatic insulin-like growth factor 1 output in vivo. Lastly, we observed potent anticancer biological efficacies of these novel hGHR antagonists against human cancer cell lines. In conclusion, we propose that these new GHR antagonists have potential for development towards multiple clinical applications related to GH-associated pathologies.

Structural modeling of cytokine-receptor-JAK2 signaling complexes using AlphaFold Multimer

Homodimeric class 1 cytokine receptors include the erythropoietin (EPOR), thrombopoietin (TPOR), granulocyte colony-stimulating factor 3 (CSF3R), growth hormone (GHR), and prolactin receptors (PRLR). They are cell-surface single-pass transmembrane (TM) glycoproteins that regulate cell growth, proliferation, and differentiation and induce oncogenesis. An active TM signaling complex consists of a receptor homodimer, one or two ligands bound to the receptor extracellular domains and two molecules of Janus Kinase 2 (JAK2) constitutively associated with the receptor intracellular domains. Although crystal structures of soluble extracellular domains with ligands have been obtained for all the receptors except TPOR, little is known about the structure and dynamics of the complete TM complexes that activate the downstream JAK-STAT signaling pathway. Three-dimensional models of five human receptor complexes with cytokines and JAK2 were generated using AlphaFold Multimer. Given the large size of the complexes (from 3220 to 4074 residues), the modeling required a stepwise assembly from smaller parts with selection and validation of the models through comparisons with published experimental data. The modeling of active and inactive complexes supports a general activation mechanism that involves ligand binding to a monomeric receptor followed by receptor dimerization and rotational movement of the receptor TM α-helices causing proximity, dimerization, and activation of associated JAK2 subunits. The binding mode of two eltrombopag molecules to TM α-helices of the active TPOR dimer was proposed. The models also help elucidating the molecular basis of oncogenic mutations that may involve non-canonical activation route. Models equilibrated in explicit lipids of the plasma membrane are publicly available.

Monobody Inhibitor Selective to the Phosphatase Domain of SHP2 and its Use as a Probe for Quantifying SHP2 Allosteric Regulation

SHP2 is a phosphatase/adaptor protein that plays an important role in various signaling pathways. Its mutations are associated with cancers and developmental diseases. SHP2 contains a protein tyrosine phosphatase (PTP) and two SH2 domains. Selective inhibition of these domains has been challenging due to the multitude of homologous proteins in the proteome. Here, we developed a monobody, synthetic binding protein, that bound to and inhibited the SHP2 PTP domain. It was selective to SHP2 PTP over close homologs. A crystal structure of the monobody-PTP complex revealed that the monobody bound both highly conserved residues in the active site and less conserved residues in the periphery, rationalizing its high selectivity. Its epitope overlapped with the interface between the PTP and N-terminal SH2 domains that is formed in auto-inhibited SHP2. By using the monobody as a probe for the accessibility of the PTP active site, we developed a simple, nonenzymatic assay for the allosteric regulation of SHP2. The assay showed that, in the absence of an activating phospho-Tyr ligand, wild-type SHP2 and the "PTP-dead" C459E mutant were predominantly in the closed state in which the PTP active site is inaccessible, whereas the E76K and C459S mutants were in the open, active state. It also revealed that previously developed monobodies to the SH2 domains, ligands lacking a phospho-Tyr, weakly favored the open state. These results provide corroboration for a conformational equilibrium underlying allosteric regulation of SHP2, provide powerful tools for characterizing and controlling SHP2 functions, and inform drug discovery against SHP2.

Isolation and Characterization of the Arapaima gigas Growth Hormone (ag-GH) cDNA and Three-Dimensional Modeling of This Hormone in Comparison with the Human Hormone (hGH)

In a previous work, the common gonadotrophic hormone α-subunit (ag-GTHα), the ag-FSH β- and ag-LH β-subunit cDNAs, were isolated and characterized by our research group from A. gigas pituitaries, while a preliminary synthesis of ag-FSH was also carried out in human embryonic kidney 293 (HEK293) cells. In the present work, the cDNA sequence encoding the ag-growth hormone (ag-GH) has also been isolated from the same giant Arapaimidae Amazonian fish. The ag-GH consists of 208 amino acids with a putative 23 amino acid signal peptide and a 185 amino acid mature peptide. The highest identity, based on the amino acid sequences, was found with the Elopiformes (82.0%), followed by Anguilliformes (79.7%) and Acipenseriformes (74.5%). The identity with the corresponding human GH (hGH) amino acid sequence is remarkable (44.8%), and the two disulfide bonds present in both sequences were perfectly conserved. Three-dimensional (3D) models of ag-GH, in comparison with hGH, were generated using the threading modeling method followed by molecular dynamics. Our simulations suggest that the two proteins have similar structural properties without major conformational changes under the simulated conditions, even though they are separated from each other by a >100 Myr evolutionary period (1 Myr = 1 million years). The sequence found will be used for the biotechnological synthesis of ag-GH while the ag-GH cDNA obtained will be utilized for preliminary Gene Therapy studies.

Mining the Protein Data Bank to improve prediction of changes in protein-protein binding

Predicting the effect of mutations on protein-protein interactions is important for relating structure to function, as well as for in silico affinity maturation. The effect of mutations on protein-protein binding energy (ΔΔG) can be predicted by a variety of atomic simulation methods involving full or limited flexibility, and explicit or implicit solvent. Methods which consider only limited flexibility are naturally more economical, and many of them are quite accurate, however results are dependent on the atomic coordinate set used. In this work we perform a sequence and structure based search of the Protein Data Bank to find additional coordinate sets and repeat the calculation on each. The method increases precision and Positive Predictive Value, and decreases Root Mean Square Error, compared to using single structures. Given the ongoing growth of near-redundant structures in the Protein Data Bank, our method will only increase in applicability and accuracy.

Divide et impera: An In Silico Screening Targeting HCMV ppUL44 Processivity Factor Homodimerization Identifies Small Molecules Inhibiting Viral Replication

Human cytomegalovirus (HCMV) is a leading cause of severe diseases in immunocompromised individuals, including AIDS patients and transplant recipients, and in congenitally infected newborns. The utility of available drugs is limited by poor bioavailability, toxicity, and emergence of resistant strains. Therefore, it is crucial to identify new targets for therapeutic intervention. Among the latter, viral protein–protein interactions are becoming increasingly attractive. Since dimerization of HCMV DNA polymerase processivity factor ppUL44 plays an essential role in the viral life cycle, being required for oriLyt-dependent DNA replication, it can be considered a potential therapeutic target. We therefore performed an in silico screening and selected 18 small molecules (SMs) potentially interfering with ppUL44 homodimerization. Antiviral assays using recombinant HCMV TB4-UL83-YFP in the presence of the selected SMs led to the identification of four active compounds. The most active one, B3, also efficiently inhibited HCMV AD169 strain in plaque reduction assays and impaired replication of an AD169-GFP reporter virus and its ganciclovir-resistant counterpart to a similar extent. As assessed by Western blotting experiments, B3 specifically reduced viral gene expression starting from 48 h post infection, consistent with the inhibition of viral DNA synthesis measured by qPCR starting from 72 h post infection. Therefore, our data suggest that inhibition of ppUL44 dimerization could represent a new class of HCMV inhibitors, complementary to those targeting the DNA polymerase catalytic subunit or the viral terminase complex.

In silico Approaches for the Design and Optimization of Interfering Peptides Against Protein-Protein Interactions

Large contact surfaces of protein-protein interactions (PPIs) remain to be an ongoing issue in the discovery and design of small molecule modulators. Peptides are intrinsically capable of exploring larger surfaces, stable, and bioavailable, and therefore bear a high therapeutic value in the treatment of various diseases, including cancer, infectious diseases, and neurodegenerative diseases. Given these promising properties, a long way has been covered in the field of targeting PPIs via peptide design strategies. In silico tools have recently become an inevitable approach for the design and optimization of these interfering peptides. Various algorithms have been developed to scrutinize the PPI interfaces. Moreover, different databases and software tools have been created to predict the peptide structures and their interactions with target protein complexes. High-throughput screening of large peptide libraries against PPIs; "hotspot" identification; structure-based and off-structure approaches of peptide design; 3D peptide modeling; peptide optimization strategies like cyclization; and peptide binding energy evaluation are among the capabilities of in silico tools. In the present study, the most recent advances in the field of in silico approaches for the design of interfering peptides against PPIs will be reviewed. The future perspective of the field and its advantages and limitations will also be pinpointed.

Interaction Energetics and Druggability of the Protein-Protein Interaction between Kelch-like ECH-Associated Protein 1 (KEAP1) and Nuclear Factor Erythroid 2 Like 2 (Nrf2)

Development of small molecule inhibitors of protein-protein interactions (PPIs) is hampered by our poor understanding of the druggability of PPI target sites. Here, we describe the combined application of alanine-scanning mutagenesis, fragment screening, and FTMap computational hot spot mapping to evaluate the energetics and druggability of the highly charged PPI interface between Kelch-like ECH-associated protein 1 (KEAP1) and nuclear factor erythroid 2 like 2 (Nrf2), an important drug target. FTMap identifies four binding energy hot spots at the active site. Only two of these are exploited by Nrf2, which alanine scanning of both proteins shows to bind primarily through E79 and E82 interacting with KEAP1 residues S363, R380, R415, R483, and S508. We identify fragment hits and obtain X-ray complex structures for three fragments via crystal soaking using a new crystal form of KEAP1. Combining these results provides a comprehensive and quantitative picture of the origins of binding energy at the interface. Our findings additionally reveal non-native interactions that might be exploited in the design of uncharged synthetic ligands to occupy the same site on KEAP1 that has evolved to bind the highly charged DEETGE binding loop of Nrf2. These include π-stacking with KEAP1 Y525 and interactions at an FTMap-identified hot spot deep in the binding site. Finally, we discuss how the complementary information provided by alanine-scanning mutagenesis, fragment screening, and computational hot spot mapping can be integrated to more comprehensively evaluate PPI druggability.

G-protein βγ subunits as multi-functional scaffolds and transducers in G-protein-coupled receptor signaling

G-protein βγ subunits are key participants in G-protein signaling. These subunits facilitate interactions between receptors and G proteins that are critical for the G protein activation cycle at the plasma membrane. In addition, they play roles in directly transducing signals to an ever expanding range of downstream targets, including integral membrane and cytosolic proteins. Emerging data indicate that Gβγ may play additional roles at intracellular compartments including endosomes, the Golgi apparatus, and the nucleus. Here, we discuss the molecular and structural basis for their ability to coordinate this wide range of cellular activities.

Structure-Activity Relationship Study on Col-003, a Protein-Protein Interaction Inhibitor between Collagen and Hsp47

This study demonstrates the structure-activity relationship of Col-003, a potent collagen-heat-shock protein 47 (Hsp47) interaction inhibitor. Col-003 analogues were successfully synthesized by Pd(0)-catalyzed cross-coupling reactions of 5-bromosalicylaldehyde derivatives with alkyl-metal species, and the inhibitory activities of the synthetic analogues were evaluated using surface plasmon resonance analysis (BIAcore). We succeeded in discovering two potent inhibitors that showed 85 and 81% inhibition at a concentration of 1.9 µM against the collagen-Hsp47 interaction. This indicates that elongation of an alkyl linker between two aromatic rings could considerably improve inhibitory activity due to the adjustment of a pendant phenyl moiety to an appropriate position, in addition to the hydrophobic interaction with an alkyl linker moiety.

Systematic profiling of clinical missence mutation effects on the intermolecular interaction between human growth hormone and its receptor in isolated growth hormone deficiency

Isolated growth hormone deficiency (IGHD) is the most common pituitary hormone deficiency and can result from congenital or acquired causes. Among the known factors, genetic mutations in human growth hormone (hGH) remain the most frequent cause of IGHD, which influence the binding of hGH to its cognate receptor (hGHbp). Although previous studies have systematically investigated the residue importance at hGH-hGHbp complex interface, the molecular role of IGHD-associated residue mutations in the complex function still remains largely unexplored. Here, a total of 21 known hGH naturally-occurring missence mutations that have been clinically observed to be involved in IGHD disorder are collected and confirmed by original literature; they effects on the conformation, energetics and dynamics of hGH-hGHbp recognition and interaction are dissected at molecular level by using atomistic dynamics simulations, binding energy calculations and fluorescence spectroscopy assays. A systematic profile of hGH-hGHbp binding response to these clinical missence mutations is created, based on which it is revealed that (i) most mutations have appreciably unfavorable effect on the binding, which potentially destabilize the complex interaction, while only very few are predicted as moderate stabilizers for the complex system, and (ii) these disease-related mutations can locate either at complex interface or in hGH protein interior far away from the interface; both can influence the complex binding through either direct interaction or indirect allostericity. Two mutations, E100K (non-interface) and G146R (interface), are identified to address potent destabilization effect on hGH-hGHbp complex system; they can reduce the complex binding affinity by 8-fold (K_d changes from 0.76 to 5.9 nM) and 46-fold (K_d changes from 0.76 to 34.7 nM), respectively.

Metal-dependent hormone function: the emerging interdisciplinary field of metalloendocrinology

For over 100 years, there has been an incredible amount of knowledge amassed concerning hormones in the endocrine system and their central role in human health. Hormones represent a diverse group of biomolecules that are released by glands, communicate signals to their target tissue, and are regulated by feedback loops to maintain organism health. Many disease states, such as diabetes and reproductive disorders, stem from misregulation or dysfunction of hormones. Increasing research is illuminating the intricate roles of metal ions in the endocrine system where they may act advantageously in concert with hormones or deleteriously catalyze hormone-associated disease states. As the critical role of metal ions in the endocrine system becomes more apparent, it is increasingly important to untangle the complex mechanisms underlying the connections between inorganic biochemistry and hormone function to understand and control endocrinological phenomena. This tutorial review harmonizes the interdisciplinary fields of endocrinology and inorganic chemistry in the newly-termed field of "metalloendocrinology". We describe examples linking metals to both normal and aberrant hormone function with a focus on highlighting insight to molecular mechanisms. Hormone activities related to both essential metal micronutrients, such as copper, iron, zinc, and calcium, and disruptive nonessential metals, such as lead and cadmium are discussed.

Conversion of Protein Active Regions into Peptidomimetic Therapeutic Leads Using Backbone Cyclization and Cycloscan - How to Do it Yourself!

Protein-protein Interactions (PPIs) are particularly important for controlling both physiologic and pathologic biological processes but are difficult to target due to their large and/or shallow interaction surfaces unsuitable for small molecules. Linear peptides found in nature interact with some PPIs, and protein active regions can be used to design synthetic peptide compounds for inhibition of PPIs. However, linear peptides are limited therapeutically by poor metabolic and conformational stability, which can compromise their bioactivity and half-life. Cyclic peptidomimetics (modified peptides) can be used to overcome these challenges because they are more resistant to metabolic degradation and can be engineered to adopt desired conformations. Backbone cyclization is a strategy that we developed to improve drug-like properties of linear peptide leads without jeopardizing the integrity of functionally relevant side-chains. Here, we provide the first description of an entire approach for developing backbone cyclized peptide compounds, based upon two straightforward 'ABC' and 'DEF' processes. We present practical examples throughout our discussion of revealing active regions important for PPIs and identifying critical pharmacophores, as well as developing backbone cyclized peptide libraries and screening them using cycloscan. Finally, we review the impact of these advances and provide a summary of current ongoing work in the field.

Surf4 (Erv29p) binds amino-terminal tripeptide motifs of soluble cargo proteins with different affinities, enabling prioritization of their exit from the endoplasmic reticulum

Some secreted proteins that assemble into large complexes, such as extracellular matrices or hormones and enzymes in storage granules, must be kept at subaggregation concentrations during intracellular trafficking. We show surfeit locus protein 4 (Surf4) is the cargo receptor that establishes different steady-state concentrations for a variety of soluble cargo proteins within the endoplasmic reticulum (ER) through interaction with the amino-terminal tripeptides exposed after removal of leader sequences. We call this motif the ER-Exit by Soluble Cargo using Amino-terminal Peptide-Encoding motif (ER-ESCAPE motif). Proteins that most readily aggregate in the ER lumen (e.g., dentin sialophosphoprotein [DSPP] and amelogenin, X-linked [AMELX]) have strong ER-ESCAPE motifs to inhibit aggregate formation, while less susceptible cargo exhibits weaker motifs. Specific changes in a single amino acid of the tripeptide result in aggregate formation and failure to efficiently traffic cargo out of the ER. A logical subset of 8,000 possible tripeptides starting a model soluble cargo protein (growth hormone) established a continuum of steady-state ER concentrations ranging from low (i.e., high affinity for receptor) to the highest concentrations associated with bulk flow-limited trafficking observed for nonbinding motifs. Human cells lacking Surf4 no longer preferentially trafficked cargo expressing strong ER-ESCAPE motifs. Reexpression of Surf4 or expression of yeast's ortholog, ER-derived vesicles protein 29 (Erv29p), rescued enhanced ER trafficking in Surf4-null cells. Hence our work describes a new way of preferentially exporting soluble cargo out of the ER that maintains proteins below the concentrations at which they form damaging aggregates.

The Growth Hormone Receptor: Mechanism of Receptor Activation, Cell Signaling, and Physiological Aspects

The growth hormone receptor (GHR), although most well known for regulating growth, has many other important biological functions including regulating metabolism and controlling physiological processes related to the hepatobiliary, cardiovascular, renal, gastrointestinal, and reproductive systems. In addition, growth hormone signaling is an important regulator of aging and plays a significant role in cancer development. Growth hormone activates the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) signaling pathway, and recent studies have provided a new understanding of the mechanism of JAK2 activation by growth hormone binding to its receptor. JAK2 activation is required for growth hormone-mediated activation of STAT1, STAT3, and STAT5, and the negative regulation of JAK-STAT signaling comprises an important step in the control of this signaling pathway. The GHR also activates the Src family kinase signaling pathway independent of JAK2. This review covers the molecular mechanisms of GHR activation and signal transduction as well as the physiological consequences of growth hormone signaling.

Hydrodynamic Steering in Protein Association Revisited: Surprisingly Minuscule Effects of Considerable Torques

We investigate the previously postulated hydrodynamic steering phenomenon, resulting from complication of molecular shapes, its magnitude and possible relevance for protein-ligand and protein-protein diffusional encounters, and the kinetics of diffusion-controlled association. We consider effects of hydrodynamic interactions in a prototypical model system consisting of a cleft enzyme and an elongated substrate, and real protein-protein complexes, that of barnase and barstar, and human growth hormone and its binding protein. The kinetics of diffusional encounters is evaluated on the basis of rigid-body Brownian dynamics simulations in which hydrodynamic interactions between molecules are modeled using the bead-shell method for detailed description of molecular surfaces, and the first-passage-time approach. We show that magnitudes of steering torques resulting from the hydrodynamic coupling of associating molecules, evaluated for the studied systems on the basis of the Stokes-Einstein type relations for arbitrarily shaped rigid bodies, are comparable with magnitudes of torques resulting from electrostatic interactions of binding partners. Surprisingly, however, unlike in the case of electrostatic torques that strongly affect the diffusional encounter, overall effects of hydrodynamic steering torques on the association kinetics, while clearly discernible in Brownian dynamics simulations, are rather minute. We explain this result as a consequence of the thermal agitation of the binding partners. Our finding is relevant for the general understanding of a wide spectrum of molecular processes in solution but there is also a more practical aspect to it if one considers the low level of shape detail of models that are usually employed to evaluate hydrodynamic interactions in particle-based Stokesian and Brownian dynamics simulations of multicomponent biomolecular systems. Results described in the current work justify, in part at least, such a low-resolution description.

Pressuromodulation at the cell membrane as the basis for small molecule hormone and peptide regulation of cellular and nuclear function

Building on recent knowledge that the specificity of the biological interactions of small molecule hydrophiles and lipophiles across microvascular and epithelial barriers, and with cells, can be predicted on the basis of their conserved biophysical properties, and the knowledge that biological peptides are cell membrane impermeant, it has been further discussed herein that cellular, and thus, nuclear function, are primarily regulated by small molecule hormone and peptide/factor interactions at the cell membrane (CM) receptors. The means of regulating cellular, and thus, nuclear function, are the various forms of CM Pressuromodulation that exist, which include Direct CM Receptor-Mediated Stabilizing Pressuromodulation, sub-classified as Direct CM Receptor-Mediated Stabilizing Shift Pressuromodulation (Single, Dual or Tri) or Direct CM Receptor-Mediated Stabilizing Shift Pressuromodulation (Single, Dual or Tri) cum External Cationomodulation (≥3+ → 1+); which are with respect to acute CM receptor-stabilizing effects of small biomolecule hormones, growth factors or cytokines, and also include Indirect CM- or CM Receptor-Mediated Pressuromodulation, sub-classified as Indirect 1ary CM-Mediated Shift Pressuromodulation (Perturbomodulation), Indirect 2ary CM Receptor-Mediated Shift Pressuromodulation (Tri or Quad Receptor Internal Pseudo-Cationomodulation: SS 1+), Indirect 3ary CM Receptor-Mediated Shift Pressuromodulation (Single or Dual Receptor Endocytic External Cationomodulation: 2+) or Indirect (Pseudo) 3ary CM Receptor-Mediated Shift Pressuromodulation (Receptor Endocytic Hydroxylocarbonyloetheroylomodulation: 0), which are with respect to sub-acute CM receptor-stabilizing effects of small biomolecules, growth factors or cytokines. As a generalization, all forms of CM pressuromodulation decrease CM and nuclear membrane (NM) compliance (whole cell compliance), due to pressuromodulation of the intracellular microtubule network and increases the exocytosis of pre-synthesized vesicular endogolgi peptides and small molecules as well as nuclear-to-rough endoplasmic reticulum membrane proteins to the CM, with the potential to simultaneously increase the NM-associated chromatin DNA transcription of higher molecular weight protein forms, secretory and CM-destined, mitochondrial and nuclear, including the highest molecular weight nuclear proteins, Ki67 (359 kDa) and Separase (230 kDa), with the latter leading to mitogenesis and cell division; while, in the case of growth factors or cytokines with external cationomodulation capability, CM Receptor External Cationomodulation of CM receptors (≥3+ → 1+) results in cationic extracellular interaction (≥3+) with extracellular matrix heparan sulfates (≥3+ → 1+) concomitant with lamellopodesis and cell migration. It can be surmised that the modulation of cellular, and nuclear, function is mostly a reactive process, governed, primarily, by small molecule hormone and peptide interactions at the cell membrane, with CM receptors and the CM itself. These insights taken together, provide valuable translationally applicable knowledge.

UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures

The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/.

Properties of the Mechanosensitive Channel MscS Pore Revealed by Tryptophan Scanning Mutagenesis

Bacterial mechanosensitive channels gate when the transmembrane turgor rises to levels that compromise the structural integrity of the cell wall. Gating creates a transient large diameter pore that allows hydrated solutes to pass from the cytoplasm at rates close to those of diffusion. In the closed conformation, the channel limits transmembrane solute movement, even that of protons. In the MscS crystal structure (Protein Data Bank entry 2oau), a narrow, hydrophobic opening is visible in the crystal structure, and it has been proposed that a vapor lock created by the hydrophobic seals, L105 and L109, is the barrier to water and ions. Tryptophan scanning mutagenesis has proven to be a highly valuable tool for the analysis of channel structure. Here Trp residues were introduced along the pore-forming TM3a helix and in selected other parts of the protein. Mutants were investigated for their expression, stability, and activity and as fluorescent probes of the physical properties along the length of the pore. Most Trp mutants were expressed at levels similar to that of the parent (MscS YFF) and were stable as heptamers in detergent in the presence and absence of urea. Fluorescence data suggest a long hydrophobic region with low accessibility to aqueous solvents, extending from L105/L109 to G90. Steady-state fluorescence anisotropy data are consistent with significant homo-Förster resonance energy transfer between tryptophan residues from different subunits within the narrow pore. The data provide new insights into MscS structure and gating.

Solvent accessible surface area-based hot-spot detection methods for protein-protein and protein-nucleic acid interfaces

Due to the importance of hot-spots (HS) detection and the efficiency of computational methodologies, several HS detecting approaches have been developed. The current paper presents new models to predict HS for protein-protein and protein-nucleic acid interactions with better statistics compared with the ones currently reported in literature. These models are based on solvent accessible surface area (SASA) and genetic conservation features subjected to simple Bayes networks (protein-protein systems) and a more complex multi-objective genetic algorithm-support vector machine algorithms (protein-nucleic acid systems). The best models for these interactions have been implemented in two free Web tools.

The structural basis of substrate recognition by the eukaryotic chaperonin TRiC/CCT

The eukaryotic chaperonin TRiC (also called CCT) is the obligate chaperone for many essential proteins. TRiC is hetero-oligomeric, comprising two stacked rings of eight different subunits each. Subunit diversification from simpler archaeal chaperonins appears linked to proteome expansion. Here, we integrate structural, biophysical, and modeling approaches to identify the hitherto unknown substrate-binding site in TRiC and uncover the basis of substrate recognition. NMR and modeling provided a structural model of a chaperonin-substrate complex. Mutagenesis and crosslinking-mass spectrometry validated the identified substrate-binding interface and demonstrate that TRiC contacts full-length substrates combinatorially in a subunit-specific manner. The binding site of each subunit has a distinct, evolutionarily conserved pattern of polar and hydrophobic residues specifying recognition of discrete substrate motifs. The combinatorial recognition of polypeptides broadens the specificity of TRiC and may direct the topology of bound polypeptides along a productive folding trajectory, contributing to TRiC's unique ability to fold obligate substrates.

Burial Level Change Defines a High Energetic Relevance for Protein Binding Interfaces

Protein-protein interfaces defined through atomic contact or solvent accessibility change are widely adopted in structural biology studies. But, these definitions cannot precisely capture energetically important regions at protein interfaces. The burial depth of an atom in a protein is related to the atom's energy. This work investigates how closely the change in burial level of an atom/residue upon complexation is related to the binding. Burial level change is different from burial level itself. An atom deeply buried in a monomer with a high burial level may not change its burial level after an interaction and it may have little burial level change. We hypothesize that an interface is a region of residues all undergoing burial level changes after interaction. By this definition, an interface can be decomposed into an onion-like structure according to the burial level change extent. We found that our defined interfaces cover energetically important residues more precisely, and that the binding free energy of an interface is distributed progressively from the outermost layer to the core. These observations are used to predict binding hot spots. Our approach's F-measure performance on a benchmark dataset of alanine mutagenesis residues is much superior or similar to those by complicated energy modeling or machine learning approaches.

Recombinant production of biologically active giant grouper (Epinephelus lanceolatus) growth hormone from inclusion bodies of Escherichia coli by fed-batch culture

Growth hormone (GH) performs important roles in regulating somatic growth, reproduction, osmoregulation, metabolism and immunity in teleosts, and thus, it has attracted substantial attention in the field of aquaculture application. Herein, giant grouper GH (ggGH) cDNA was cloned into the pET28a vector and expressed in Shuffle® T7 Competent Escherichia coli. Recombinant N-terminal 6× His-tagged ggGH was produced mainly in insoluble inclusion bodies; the recombinant ggGH content reached 20% of total protein. For large-scale ggGH production, high-cell density E. coli culture was achieved via fed-batch culture with pH-stat. After 30h of cultivation, a cell concentration of 41.1g/l dry cell weight with over 95% plasmid stability was reached. Maximal ggGH production (4.0g/l; 22% total protein) was achieved via mid-log phase induction. Various centrifugal forces, buffer pHs and urea concentrations were optimized for isolation and solubilization of ggGH from inclusion bodies. Hydrophobic interactions and ionic interactions were the major forces in ggGH inclusion body formation. Complete ggGH inclusion body solubilization was obtained in PBS buffer at pH 12 containing 3M urea. Through a simple purification process including Ni-NTA affinity chromatography and refolding, 5.7mg of ggGH was obtained from 10ml of fed-batch culture (45% recovery). The sequence and secondary structure of the purified ggGH were confirmed by LC-MS/MS mass spectrometry and circular dichroism analysis. The cell proliferation-promoting activity was confirmed in HepG2, ZFL and GF-1 cells with the WST-1 colorimetric bioassay.

A new scoring function for protein-protein docking that identifies native structures with unprecedented accuracy

Protein-protein (P-P) 3D structures are fundamental to structural biology and drug discovery. However, most of them have never been determined. Many docking algorithms were developed for that purpose, but they have a very limited accuracy in generating native-like structures and identifying the most correct one, in particular when a single answer is asked for. With such a low success rate it is difficult to point out one docked structure as being native-like. Here we present a new, high accuracy, scoring method to identify the 3D structure of P-P complexes among a set of trial poses. It incorporates alanine scanning mutagenesis experimental data that need to be obtained a priori. The scoring scheme works by matching the computational and the experimental alanine scanning mutagenesis results. The size of the trial P-P interface area is also taken into account. We show that the method ranks the trial structures and identifies the native-like structures with unprecedented accuracy (∼94%), providing the correct P-P 3D structures that biochemists and molecular biologists need to pursue their studies. With such a success rate, the bottleneck of protein-protein docking moves from the scoring to searching algorithms.

A new mechanism for growth hormone receptor activation of JAK2, and implications for related cytokine receptors

The growth hormone receptor was the first cytokine receptor to be cloned and crystallized, and provides a valuable exemplar for activation of its cognate kinase, JAK2. We review progress in understanding its activation mechanism, in particular the molecular movements made by this constitutively dimerized receptor in response to ligand binding, and how these lead to a separation of JAK-binding Box1 motifs. Such a separation leads to removal of the pseudokinase inhibitory domain from the kinase domain of a partner JAK2 bound to the receptor, and vice versa, leading to apposition of the kinase domains and transactivation. This may be a general mechanism for class I cytokine receptor action.

Oncogenic protein interfaces: small molecules, big challenges

Historically, targeting protein-protein interactions with small molecules was not thought possible because the corresponding interfaces were considered mostly flat and featureless and therefore 'undruggable'. Instead, such interactions were targeted with larger molecules, such as peptides and antibodies. However, the past decade has seen encouraging breakthroughs through the refinement of existing techniques and the development of new ones, together with the identification and exploitation of unexpected aspects of protein-protein interaction surfaces. In this Review, we describe some of the latest techniques to discover modulators of protein-protein interactions and how current drug discovery approaches have been adapted to successfully target these interfaces.

Total synthesis and characterization of thielocin B1 as a protein–protein interaction inhibitor of PAC3 homodimer

We have characterized the inhibition of the protein–protein interaction of the homodimer of proteasome assembling chaperone (PAC) 3 with thielocin B1.

Applying physics-based scoring to calculate free energies of binding for single amino acid mutations in protein-protein complexes

Predicting changes in protein binding affinity due to single amino acid mutations helps us better understand the driving forces underlying protein-protein interactions and design improved biotherapeutics. Here, we use the MM-GBSA approach with the OPLS2005 force field and the VSGB2.0 solvent model to calculate differences in binding free energy between wild type and mutant proteins. Crucially, we made no changes to the scoring model as part of this work on protein-protein binding affinity--the energy model has been developed for structure prediction and has previously been validated only for calculating the energetics of small molecule binding. Here, we compare predictions to experimental data for a set of 418 single residue mutations in 21 targets and find that the MM-GBSA model, on average, performs well at scoring these single protein residue mutations. Correlation between the predicted and experimental change in binding affinity is statistically significant and the model performs well at picking "hotspots," or mutations that change binding affinity by more than 1 kcal/mol. The promising performance of this physics-based method with no tuned parameters for predicting binding energies suggests that it can be transferred to other protein engineering problems.

Solvent-accessible surface area: How well can be applied to hot-spot detection?

A detailed comprehension of protein-based interfaces is essential for the rational drug development. One of the key features of these interfaces is their solvent accessible surface area profile. With that in mind, we tested a group of 12 SASA-based features for their ability to correlate and differentiate hot- and null-spots. These were tested in three different data sets, explicit water MD, implicit water MD, and static PDB structure. We found no discernible improvement with the use of more comprehensive data sets obtained from molecular dynamics. The features tested were shown to be capable of discerning between hot- and null-spots, while presenting low correlations. Residue standardization such as rel SASAi or rel/res SASAi , improved the features as a tool to predict ΔΔGbinding values. A new method using support machine learning algorithms was developed: SBHD (Sasa-Based Hot-spot Detection). This method presents a precision, recall, and F1 score of 0.72, 0.81, and 0.76 for the training set and 0.91, 0.73, and 0.81 for an independent test set.

Characterizing changes in the rate of protein-protein dissociation upon interface mutation using hotspot energy and organization

Predicting the effects of mutations on the kinetic rate constants of protein-protein interactions is central to both the modeling of complex diseases and the design of effective peptide drug inhibitors. However, while most studies have concentrated on the determination of association rate constants, dissociation rates have received less attention. In this work we take a novel approach by relating the changes in dissociation rates upon mutation to the energetics and architecture of hotspots and hotregions, by performing alanine scans pre- and post-mutation. From these scans, we design a set of descriptors that capture the change in hotspot energy and distribution. The method is benchmarked on 713 kinetically characterized mutations from the SKEMPI database. Our investigations show that, with the use of hotspot descriptors, energies from single-point alanine mutations may be used for the estimation of off-rate mutations to any residue type and also multi-point mutations. A number of machine learning models are built from a combination of molecular and hotspot descriptors, with the best models achieving a Pearson's Correlation Coefficient of 0.79 with experimental off-rates and a Matthew's Correlation Coefficient of 0.6 in the detection of rare stabilizing mutations. Using specialized feature selection models we identify descriptors that are highly specific and, conversely, broadly important to predicting the effects of different classes of mutations, interface regions and complexes. Our results also indicate that the distribution of the critical stability regions across protein-protein interfaces is a function of complex size more strongly than interface area. In addition, mutations at the rim are critical for the stability of small complexes, but consistently harder to characterize. The relationship between hotregion size and the dissociation rate is also investigated and, using hotspot descriptors which model cooperative effects within hotregions, we show how the contribution of hotregions of different sizes, changes under different cooperative effects.

Computational Alanine Scanning Mutagenesis-An Improved Methodological Approach for Protein-DNA Complexes

Proteins and protein-based complexes are the basis of many key systems in nature and have been the subject of intense research in the last decades, in an attempt to acquire comprehensive knowledge of reactions that take place in nature. Computational Alanine Scanning Mutagenesis approaches have been extensively used in the study of protein interfaces and in the determination of the most important residues for complex formation, the Hot-spots. However, as it is usually applied to the study of protein-protein interfaces, we tried to modify and apply it to the study of protein-DNA interfaces, which are also crucial in nature but have not been the subject of as much research. In this work, we carry out MD simulations of seven protein-DNA complexes and tested the influence of the variation of different parameters on the determination of the binding free energy terms (ΔΔGbinding) of 78 mutations: solvent representation, internal dielectric constant, Linear and Nonlinear Poisson-Boltzmann equation, Generalized Born model, simulation time, number of structures analyzed, number of MD trajectories, force field used, and energetic terms involved. Overall, this new approach gave an average error of 1.55 kcal/mol, and P, R, F1, accuracy, and specificity values of 0.78, 0.50, 0.61, 0.77, and 0.92, respectively. This improved computational alanine scanning mutagenesis approach may serve as a tool to explore the behavior of this important class of complexes.

Hot-spot mapping of the interactions between chymosin and bovine κ-casein

Chymosin is a commercially important enzyme in the manufacturing of cheese. Chymosin cleaves the milk protein κ-casein, which initiates the clotting process. Recently, it has been shown that camel chymosin has superior enzymatic properties toward cow's milk, compared to bovine chymosin. The two enzymes possess a high degree of homology. There are only minor differences in the binding cleft; hence, these must be important for binding the substrate. Models for the binding of a 16 amino acid fragment, consisting of the chymosin-sensitive region of bovine κ-casein (97-112), to both enzymes have previously been presented. Computational alanine scanning for mutating 39 residues in the substrate and the bovine enzyme are presented herein, and warm- (ΔΔG > 1 kcal/mol) and hot-spot (ΔΔG > 2 kcal/mol) residues in the bovine enzyme are identified. These residues are relevant for site-directed mutagenesis, with the aim of modifying the binding affinity and in turn affecting the catalytic efficacy of the enzyme.

Deregulations in the cyclin-dependent kinase-9-related pathway in cancer: implications for drug discovery and development

The CDK9-related pathway is an important regulator of mammalian cell biology and is also involved in the replication cycle of several viruses, including the human immunodeficiency virus type 1. CDK9 is present in two isoforms termed CDK9-42 and CDK9-55 that bind noncovalently type T cyclins and cyclin K. This association forms a heterodimer, where CDK9 carries the enzymatic site and the cyclin partner functions as a regulatory subunit. This heterodimer is the main component of the positive transcription elongation factor b, which stabilizes RNA elongation via phosphorylation of the RNA pol II carboxyl terminal domain. Abnormal activities in the CDK9-related pathway were observed in human malignancies and cardiac hypertrophies. Thus, the elucidation of the CDK9 pathway deregulations may provide useful insights into the pathogenesis and progression of human malignancies, cardiac hypertrophy, AIDS and other viral-related maladies. These studies may lead to the improvement of kinase inhibitors for the treatment of the previously mentioned pathological conditions. This review describes the CDK9-related pathway deregulations in malignancies and the development of kinase inhibitors in cancer therapy, which can be classified into three categories: antagonists that block the ATP binding site of the catalytic domain, allosteric inhibitors, and small molecules that disrupt protein-protein interactions.

Identification of the β-lactamase inhibitor protein-II (BLIP-II) interface residues essential for binding affinity and specificity for class A β-lactamases

The interactions between β-lactamase inhibitory proteins (BLIPs) and β-lactamases have been used as model systems to understand the principles of affinity and specificity in protein-protein interactions. The most extensively studied tight binding inhibitor, BLIP, has been characterized with respect to amino acid determinants of affinity and specificity for binding β-lactamases. BLIP-II, however, shares no sequence or structural homology to BLIP and is a femtomolar to picomolar potency inhibitor, and the amino acid determinants of binding affinity and specificity are unknown. In this study, alanine scanning mutagenesis was used in combination with determinations of on and off rates for each mutant to define the contribution of residues on the BLIP-II binding surface to both affinity and specificity toward four β-lactamases of diverse sequence. The residues making the largest contribution to binding energy are heavily biased toward aromatic amino acids near the center of the binding surface. In addition, substitutions that reduce binding energy do so by increasing off rates without impacting on rates. Also, residues with large contributions to binding energy generally exhibit low temperature factors in the structures of complexes. Finally, with the exception of D206A, BLIP-II alanine substitutions exhibit a similar trend of effect for all β-lactamases, i.e., a substitution that reduces affinity for one β-lactamase usually reduces affinity for all β-lactamases tested.

Comprehensive experimental and computational analysis of binding energy hot spots at the NF-κB essential modulator/IKKβ protein-protein interface

We report a comprehensive analysis of binding energy hot spots at the protein-protein interaction (PPI) interface between nuclear factor kappa B (NF-κB) essential modulator (NEMO) and IκB kinase subunit β (IKKβ), an interaction that is critical for NF-κB pathway signaling, using experimental alanine scanning mutagenesis and also the FTMap method for computational fragment screening. The experimental results confirm that the previously identified NEMO binding domain (NBD) region of IKKβ contains the highest concentration of hot-spot residues, the strongest of which are W739, W741, and L742 (ΔΔG = 4.3, 3.5, and 3.2 kcal/mol, respectively). The region occupied by these residues defines a potentially druggable binding site on NEMO that extends for ~16 Å to additionally include the regions that bind IKKβ L737 and F734. NBD residues D738 and S740 are also important for binding but do not make direct contact with NEMO, instead likely acting to stabilize the active conformation of surrounding residues. We additionally found two previously unknown hot-spot regions centered on IKKβ residues L708/V709 and L719/I723. The computational approach successfully identified all three hot-spot regions on IKKβ. Moreover, the method was able to accurately quantify the energetic importance of all hot-spot residues involving direct contact with NEMO. Our results provide new information to guide the discovery of small-molecule inhibitors that target the NEMO/IKKβ interaction. They additionally clarify the structural and energetic complementarity between "pocket-forming" and "pocket-occupying" hot-spot residues, and further validate computational fragment mapping as a method for identifying hot spots at PPI interfaces.

Discovery of ABT-263, a Bcl-family protein inhibitor: observations on targeting a large protein-protein interaction

BACKGROUND

The discovery of ABT-263, a rationally designed Bcl-2/Bcl-xL inhibitor at present in Phase I clinical trials for cancer, is described. Emphasis is placed on the specific hurdles overcome throughout the discovery process that relate to the nature of the targeted protein-protein interaction (PPI).

OBJECTIVE/METHODS

This review draws on observations from the experience of discovering ABT-263 and discusses them within the framework of the larger issue of discovering drugs targeting PPIs. Issues discussed include the 'hot spot' paradigm, hit and lead generation, serum protein binding, structure-based design, and in particular, hydrophobicity and molecular size and their relation to pharmacokinetic/pharmacodynamic properties.

RESULTS/CONCLUSION

Approaches to understanding obstacles thought of as being specifically attached to PPIs, and existing techniques to combat these obstacles, were very helpful in overcoming them. The example of ABT-263 provides evidence that the larger family of PPI targets is more tractable than may have been thought.

Short stature in two siblings heterozygous for a novel bioinactive GH mutant (GH-P59S) suggesting that the mutant also affects secretion of the wild-type GH

OBJECTIVE

Short stature caused by biologically inactive GH is clinically characterized by lack of GH action despite normal-high secretion of GH, pathologically low IGF1 concentrations and marked catch-up growth on GH replacement therapy.

DESIGN AND METHODS

Adopted siblings (girl and a boy) of unknown family history were referred for assessment of short stature (-4.5 and -5.6 SDS) at the age of 10 and 8.1 years respectively. They had delayed bone ages (6.8 and 4.5 years), normal GH peaks at stimulation tests, and severely reduced IGF1 concentrations (-3.5 and -4.0 SDS). Genetic analysis of the GH1 gene showed a heterozygous P59S mutation at position involved in binding to GH receptor (GHR).

RESULTS

Isoelectric focusing analysis of secreted GH in patient serum revealed the presence of higher GH-P59S peak compared with that of wt-GH. Furthermore, computational simulation of GH-P59S binding to GHR suggested problems in correct binding of the mutant to the GHR. In vitro GHR binding studies revealed reduced binding affinity of GH-P59S for GHR (IC₅₀, 30  ng/ml) when compared with the wt-GH (IC₅₀, 11.8  ng/ml) while a significantly decreased ability of the mutant to activate the Jak2/Stat5 signaling pathway was observed at physiological concentrations of 25-100  ng/ml.

CONCLUSIONS

The clinical and biochemical data of our patients support the diagnosis of partial bioinactive GH syndrome. The higher amount of GH-P59S secreted in their circulation combined with its impact on the wt-GH function on GHR binding and signaling may alter GHR responsiveness to wt-GH and could ultimately explain severe short stature found in our patients.

Growth hormone from striped catfish (Pangasianodon hypophthalmus): genomic organization, recombinant expression and biological activity

Growth hormone is an essential polypeptide required for normal growth and development of vertebrates. In this report, striped catfish (Pangasianodon hypophthalmus) growth hormone gene and cDNA were isolated by reverse transcriptase-polymerase chain reaction. The striped catfish growth hormone (scGH) encoding gene contains 5 exons and 4 introns. The cDNA sequence of the scGH gene contains a 603bp open reading frame and encodes for a 200-aa protein consisting of a putative 22-aa signal peptide and the mature 178-aa protein. The recombinant histidine-tagged scGH protein which expressed in Escherichia coli as inclusion bodies was unfolded, refolded and purified to near-homogeneity by Ni(2+)-NTA chromatography. Analysis of the secondary structure content by CD spectroscopy showed that the α-helical content of the refolded scGH is 55%. Elucidation of the folding pathway of scGH by fluorescence spectroscopy showed that denaturation transition of scGH is coincident and cooperative, consistent with the two-state denaturation mechanism. The purified scGH was biologically active and exhibited growth-promoting activity in striped catfish, but not tilapia.